Key skills
Artificial IntelligenceMachine LearningGenerative AILarge Language Models (LLMs)Retrieval-Augmented Generation (RAG)Amazon BedrockAWS AI servicesCloud architectureDevSecOps practicesREST APIsHealthcare interoperability standards FHIRHealthcare interoperability standards HL7Healthcare interoperability standards CCDRisk managementSoftware delivery lifecycleAgile Software Development (Scrum/Kanban)Prompt engineeringSource groundingHallucination testingHuman validationAI evaluation methodologiesProject Management Professional (PMP)PMI-ACPCertified Scrum Master (CSM)SAFe certificationResponsible AINIST AI Risk Management Framework (AI RMF)NIST SP 800-53FISMAFedRAMPSNOMED CTICD-10RxNormLOINCProject managementAILarge Language ModelsRAGAWSBedrockAgileScrumKanbanSDLCLeadershipProject ManagementRisk ManagementCommunicationCollaborationPresentation Skills
About this role
VetsEZ is seeking a Senior AI Project Manager to lead the successful delivery of enterprise Artificial Intelligence (AI) solutions supporting the Department of Veterans Affairs (VA). This role involves planning, executing, and delivering AI software development projects while ensuring compliance with Federal security and governance requirements.
Responsibilities:
- Lead planning, execution, and delivery of enterprise AI software development projects supporting VA healthcare initiatives
- Develop and manage integrated project schedules, milestones, deliverables, resource plans, and roadmaps, including clinical validation, governance, security, and approval dependencies
- Manage project scope, risks, issues, assumptions, dependencies, and change requests, including decisions requiring Government approval
- Ensure project execution aligns with contractual requirements, business priorities, and delivery objectives
- Provide leadership that promotes collaboration, accountability, and continuous improvement across multidisciplinary teams
- Lead delivery of Generative AI solutions utilizing Retrieval-Augmented Generation (RAG) architectures and Large Language Models (LLMs)
- Coordinate activities between Government stakeholders, clinicians, architects, engineers, cybersecurity teams, privacy and AI governance stakeholders, and product owners
- Facilitate discovery sessions, requirements validation, solution demonstrations, and clinical feedback sessions
- Coordinate AI governance, Responsible AI, Human-in-the-Loop (HITL), security, privacy, and clinical validation activities
- Ensure AI capabilities align with clinical workflows, business objectives, and approved MVP scope, with measurable acceptance criteria for quality, source traceability, clinical relevance, latency, and clinician feedback
- Provide delivery oversight across Agile teams, ensuring sprint plans, dependencies, milestones, and release objectives align with the project roadmap
- Partner with Product Owners and Scrum Masters to support Agile planning, refinement, reviews, and retrospectives
- Monitor sprint progress, delivery metrics, and release readiness
- Coordinate resolution of cross-team impediments requiring Government, security, governance, clinical, or architectural decisions
- Coordinate test-environment readiness, clinical evaluation, and future transition planning with Government stakeholders
- Monitor project risks, technical dependencies, and schedule impacts while developing mitigation strategies
- Coordinate activities supporting Federal cybersecurity, privacy, AI governance, clinical validation, and Authority to Operate (ATO) planning
- Ensure compliance with applicable VA Software Development Lifecycle (SDLC), security, and operational requirements
- Support project reporting, audit readiness, governance readiness, and executive decision-making through accurate documentation and status reporting
- Prepare executive briefings, project status reports, dashboards, and milestone updates
- Present project progress, risks, dependencies, and recommendations to executive leadership and Government customers
- Communicate complex technical concepts effectively to both technical and non-technical audiences
- Foster strong customer relationships through proactive communication and collaboration
Requirements:
- Bachelor's degree in Computer Science, Information Technology, Business, Healthcare Informatics, or a related field, or equivalent experience
- 10+ years leading enterprise software development projects
- 5+ years managing Agile software development teams delivering cloud-based applications
- Demonstrated experience leading Artificial Intelligence, Machine Learning, or Generative AI capabilities through development, evaluation, and formal approval
- Experience delivering AWS cloud applications using Amazon Bedrock or similar AI platforms
- Experience leading cross-functional teams in regulated healthcare or Federal environments
- Agile Software Development (Scrum/Kanban)
- Generative AI, Large Language Models (LLMs), and Retrieval-Augmented Generation (RAG) delivery lifecycles
- Amazon Bedrock and AWS AI services
- Prompt engineering, source grounding, hallucination testing, human validation, and AI evaluation methodologies
- Cloud architecture and DevSecOps practices
- REST APIs and enterprise system integration
- Healthcare interoperability standards (FHIR, HL7, CCD)
- Risk management and software delivery lifecycle
- Strong leadership, organizational, and project management skills
- Excellent communication and presentation skills with experience briefing executive leadership and Government stakeholders
- Experience coordinating multidisciplinary engineering, cybersecurity, infrastructure, and clinical teams
- Strong analytical, problem-solving, and decision-making abilities
- Ability to manage multiple priorities in a fast-paced Agile environment
- Ability to obtain and maintain a Government Public Trust clearance
- Project Management Professional (PMP), PMI-ACP, Certified Scrum Master (CSM), or SAFe certification
- Experience supporting the Department of Veterans Affairs (VA), Department of Defense (DoD), or other Federal healthcare organizations
- Experience delivering AI-enabled clinical workflow, search, summarization, or clinician-support capabilities requiring human validation
- Knowledge of Responsible AI, NIST AI Risk Management Framework (AI RMF), NIST SP 800-53, FISMA, and FedRAMP
- Familiarity with clinical terminology standards including SNOMED CT, ICD-10, RxNorm, and LOINC
- AWS Cloud, AI, or Machine Learning certifications are highly desirable